Spectr: An MCP That Writes App Specs from Screen Recordings for Pixel-Perfect Claude Clones
u/thanpolas' post "the trick was the spec, not the prompts" hit home for many developers using Claude to clone iOS apps. The bottleneck wasn't prompting — it was describing the UI. Each screen required ~30 minutes of prose, and Claude would still get it wrong, requiring three iterations per screen.
Enter Spectr — an MCP (Model Context Protocol) tool that takes any .mp4 or .mov recording of an iOS app and outputs a spec.md automatically. The Vision processing runs through your Claude subscription (no separate API key needed). Each recording takes 5–10 minutes to process.
What the Spec Contains
The generated spec is a 7-section document covering:
- Exact hex color codes
- Exact font weights
- Exact spacing values
- Every screen state
- Every transition
- Component inventory
- Navigation graph
This level of detail is precise enough that Claude's /goal mode can produce a pixel-perfect clone unattended.
Three Install Surfaces
Spectr ships as:
- MCP server — works in Claude Code, Claude Desktop, and any MCP-compatible host
- CLI — run
spectr ./recording.mp4 ./spec.md - Claude Code skill — triggered with natural language, no command memorization
The project is by u/Working-Middle2582. A gallery of real specs produced from real iOS apps is available at spectr.to/gallery. The author is asking for honest feedback — no hype, just roast it.
This is a practical solution for anyone who's tired of spending hours manually documenting UI specs for AI coding agents. If you've been cloning apps with Claude, the spec, not the prompt, was likely your bottleneck.
📖 Read the full source: r/ClaudeAI
👀 See Also
Open Source Knowledge Base Server and Multi-Agent Orchestrator for Persistent AI Memory
A developer built a custom MCP server on a private VPS to give Claude, Codex, and Gemini persistent memory across sessions, with a knowledge base server that ingests Obsidian vaults and a multi-agent orchestrator called Daniel for failover.
Task-observer: A Meta-Skill That Automates Skill Improvement for AI Coding Agents
Task-observer is a meta-skill that self-improves all your AI agent's skills, including itself. It logged 600 skill improvements across 40 skills in 3 months and automates skill creation from work gaps.
Claude Code's Illusion of Finished Work: Why Reviewing the Agent's Path Matters More Than the Diff
Claude Code can produce a clean diff, passing tests, and a good summary—yet still miss real behavior, security concerns, or architecture constraints. The author argues that reviewing the chain of actions (plans, files read, commands run, test output) is now essential, not just the final diff.
Hollow Agent OS: Local AI workers call Claude as senior architect when stuck
Hollow Agent OS uses local Qwen models that run 24/7, but when they hit logic errors or need major changes, they trigger a Claude call via MCP. Claude reorganizes file structures, reviews code, and acts as a manager for autonomous local workers.